
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "185"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 75 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 71 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.825789	-0.705340	3.755895	-0.064420	26.117440	-1.094899	5.087134	-0.228373	0.7901	0.7921	0.2590	9.985581	10.487321
2459593	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.600336	-0.330763	8.082918	-0.388030	2.398309	-0.827094	1.447237	-0.253636	0.7287	0.7309	0.2560	6.643827	6.242849
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.657932	-0.649033	1.493445	-0.648710	1.697433	-0.581695	1.238847	-0.145683	0.0414	0.0404	0.0010	nan	nan
2459591	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.100344	-0.716055	9.273332	0.394884	1.832628	-0.685043	-1.050804	0.177298	0.6769	0.6882	0.3724	9.241232	7.838537
2459590	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.612646	-0.184104	8.363104	-0.238750	1.851746	-0.932355	-0.733957	-0.094895	0.6802	0.6868	0.3626	7.883886	6.904780
2459589	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.283712	-0.615113	6.571590	-0.348904	12.090117	-0.943449	3.361880	-0.516967	0.7209	0.7159	0.2803	6.531228	5.940619
2459588	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.745419	-0.858900	10.081901	0.033571	1.628107	-0.666296	2.577283	-0.409014	0.7695	0.7526	0.2397	7.970378	7.709468
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	1.839885	-0.464875	13.971842	0.705275	1.450743	0.030297	-0.540765	0.379965	nan	nan	nan	26.829630	26.930296
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	7.03%	0.00%	0.454876	-0.363374	0.256344	-0.380046	-0.772545	-0.997408	-0.630407	0.918717	0.6697	0.6826	0.3522	1.689472	1.665518
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.360295	0.364892	-0.123794	0.535734	1.342511	0.185320	1.459289	-0.173440	0.0416	0.0419	0.0016	0.000000	0.000000
2459584	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.60%	1.803181	0.593521	-0.698837	-0.253084	-0.617867	-0.573188	-0.379346	2.090145	0.6213	0.6283	0.3643	1.413542	1.426742
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	3.23%	0.00%	0.849597	0.083471	-0.854513	0.609160	-0.526303	-0.403183	-0.469334	1.496027	0.6830	0.6893	0.3808	1.767551	1.852674
2459582	digital_ok	0.00%	0.00%	0.00%	0.00%	2.70%	0.00%	0.668363	0.233064	-0.473784	0.830849	-0.823557	-0.659074	-0.572094	0.119594	0.6838	0.6908	0.3853	1.707266	1.721474
2459581	digital_ok	0.00%	0.00%	0.00%	0.00%	3.24%	0.00%	0.689061	0.339392	-0.965928	0.323746	-0.835010	-0.559343	-0.494578	2.312446	0.6867	0.6939	0.3830	1.676514	1.654820
2459580	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	0.654798	0.215109	-0.460488	0.428187	-0.643938	-0.463555	-0.626422	2.707840	0.6852	0.6910	0.3811	1.776067	1.708207
2459579	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459578	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.509440	-0.380258	-0.846471	-0.814087	1.113495	0.469251	-0.398053	-0.657530	0.0327	0.0349	0.0017	nan	nan
2459577	digital_ok	0.00%	0.00%	0.00%	0.00%	17.84%	3.24%	0.450756	0.010835	-0.897200	0.376623	-0.611257	-0.388771	-0.294326	0.691915	0.6799	0.6871	0.3847	1.718525	1.657772
2459576	digital_ok	0.00%	0.00%	0.00%	0.00%	4.84%	0.00%	0.075341	0.107190	-0.739469	0.644148	-0.307691	0.984270	-0.348522	3.341943	0.7055	0.7128	0.3794	1.501817	1.546806
2459575	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.178435	0.084790	-0.348930	0.430159	11.260325	-0.328422	-0.851540	0.376508	0.7661	0.7682	0.3224	8.838306	9.059340
2459574	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459573	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459572	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	0.760989	0.567229	-0.719414	0.452953	-0.773821	0.103615	-0.345827	-0.313317	0.7048	0.7145	0.3842	1.584584	1.563755
2459571	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.345986	-0.386905	-0.877728	-0.904304	6.325330	-0.696261	-0.085765	-0.416918	0.0379	0.0464	0.0013	nan	nan
2459570	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	3.24%	0.679373	0.998178	0.440904	0.901157	0.597869	0.723186	0.409852	0.739308	0.6918	0.7056	0.3470	1.583710	1.752035
2459569	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	0.411454	0.126475	-0.838659	0.423020	0.906575	0.261656	-0.715361	0.446398	0.7839	0.7872	0.2206	2.050450	1.919016
2459566	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	0.624731	-0.075986	-0.734560	0.537676	0.060752	0.172023	0.635900	3.275805	0.6944	0.7055	0.3943	1.637507	1.679306
2459565	digital_ok	0.00%	-	-	-	100.00%	0.00%	0.190615	0.190615	0.168786	0.168786	-0.882853	-0.882853	-0.945292	-0.945292	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	0.00%	0.00%	0.00%	0.00%	5.20%	0.00%	-0.249120	0.714994	-1.059075	0.839374	-0.080625	-0.002746	0.391342	3.345516	0.7120	0.7117	0.3982	1.745634	1.669960
2459563	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	1.087594	0.118621	-0.316655	-0.077197	-0.171061	-0.518753	-0.111014	1.076474	0.7077	0.7124	0.3872	1.697740	1.723815
2459562	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.147365	0.764805	-0.366573	0.651318	0.295087	0.730140	-0.010546	1.725612	0.7129	0.7180	0.3829	1.776684	1.714619
2459561	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	0.507134	0.576863	-0.415935	0.451852	0.613700	0.433523	0.089609	0.102760	0.7101	0.7171	0.3828	1.847096	1.793254
2459560	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.002274	0.370337	-0.310425	0.515613	0.734614	0.618890	0.042274	0.006580	0.7052	0.7120	0.3968	1.694051	1.649114
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.232071	0.421616	-0.497187	0.420295	0.586156	0.439499	0.229354	1.242312	0.7076	0.7120	0.3832	1.724665	1.615365
2459558	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0380	0.0405	0.0021	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	5.41%	0.00%	0.923991	0.474062	-0.535343	1.113720	-0.615938	-0.407899	-0.623517	0.595015	0.7048	0.7062	0.3944	1.641284	1.556332
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7133	0.7160	0.3956	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7022	0.6877	0.3891	nan	nan
2459552	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	6.130652	7.122553	0.364813	1.381369	49.498931	11.870497	1.437761	1.292092	0.7078	0.7043	0.3894	10.328940	9.759193
2459551	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.005495	0.286895	-0.616673	0.453451	0.574708	0.597986	-0.068835	0.725186	0.7115	0.7135	0.3896	1.854084	1.721490
2459550	digital_ok	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0516	0.0515	0.0007	nan	nan
2459549	digital_ok	0.00%	0.00%	0.00%	0.00%	8.11%	0.00%	1.216991	0.052314	-0.671469	0.250221	-0.164155	-0.372189	-0.145811	1.631243	0.7063	0.7063	0.4037	1.766616	1.605004
2459542	digital_ok	0.00%	0.00%	0.00%	0.00%	22.32%	0.00%	1.035348	0.668684	-0.811164	1.382464	-0.721124	-0.608814	-0.400267	1.633872	0.7632	0.7530	0.3553	1.713527	1.632917
2459541	digital_ok	0.00%	0.45%	0.45%	0.00%	21.88%	0.00%	0.236534	-0.222132	-0.038978	0.269578	-0.080061	0.076131	-0.676052	0.672930	0.7646	0.7542	0.3277	1.690285	1.573149
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	21.88%	0.89%	0.521367	0.609764	-0.575650	0.425592	-0.574016	-0.168944	-0.289149	0.507984	0.7662	0.7562	0.3389	1.619774	1.521556
2459536	digital_ok	0.00%	0.00%	0.00%	0.00%	5.93%	0.00%	-0.193369	0.122355	-0.014732	0.894009	-0.820329	-0.766732	-0.510580	-0.818114	0.7348	0.7333	0.4292	1.816158	1.628359
2459535	digital_ok	0.00%	0.00%	0.00%	0.00%	21.43%	0.00%	0.177201	0.170730	-0.410262	0.350455	-0.699093	-0.036196	-0.391259	-0.351709	0.8004	0.7775	0.3618	1.851252	1.592338
2459534	digital_ok	100.00%	98.66%	98.66%	0.00%	100.00%	0.00%	4.400572	3.736147	-1.014179	-0.615410	2.418209	4.344867	8.298752	8.307062	0.0854	0.1128	0.0203	1.298762	1.282358
2459533	digital_ok	0.00%	0.00%	0.00%	0.00%	4.89%	0.00%	0.456619	0.026149	-0.425169	0.203273	-0.372534	-0.399636	-0.699797	-0.500117	0.7342	0.7274	0.4065	1.794598	1.665966
2459532	digital_ok	0.00%	0.00%	0.00%	0.00%	5.00%	0.00%	0.478881	0.381987	-0.275938	1.050020	-1.312133	-0.813592	-0.876907	-0.324902	0.7350	0.7322	0.4076	1.766440	1.682954
2459530	digital_ok	0.00%	0.00%	0.00%	0.00%	4.73%	0.00%	-0.194503	0.209481	-0.433480	0.352552	0.365775	0.776714	-0.105673	0.099310	0.7528	0.7431	0.3987	1.838016	1.669791
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.189759	0.350679	-0.714963	0.689410	0.269386	-1.040785	-0.561327	0.125990	0.9069	0.9324	0.2986	0.000000	0.000000
2459523	digital_ok	0.00%	-	-	-	14.29%	0.00%	1.299544	-0.043446	-1.032494	0.642259	-0.880650	-0.804439	-0.748904	-0.348673	nan	nan	nan	2.424692	2.164154
2459522	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.00%	0.838659	0.094889	-0.272126	0.711436	-1.534346	-0.281603	-0.713892	0.157666	0.7242	0.6938	0.3347	1.971538	2.136777
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.174272	-0.377226	-0.799319	-0.799403	-0.794118	-1.076251	-0.807713	-0.662751	0.0357	0.0403	0.0013	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	0.523074	0.499840	-1.003665	0.419746	-0.894682	-0.529241	-1.119971	0.076427	0.9178	0.9460	0.1696	0.000000	0.000000
2459505	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.245871	0.727724	0.181334	1.005246	-1.030507	-0.242462	-0.012624	1.118808	0.0543	0.0563	0.0028	1.269035	1.249893
2459503	digital_ok	0.00%	0.00%	0.00%	0.00%	89.47%	0.00%	0.490806	0.355609	-0.087623	0.773140	-0.355513	1.517384	-0.208595	1.260895	0.8664	0.8611	0.4390	0.000000	0.000000
2459501	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.466318	-0.111821	-0.081146	-0.058324	0.930940	-0.731170	-0.693507	-0.235600	0.1085	0.1227	0.0114	0.000000	0.000000
2459500	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.075155	-0.326436	-1.044279	-0.321964	-0.408506	-0.129318	-0.509850	-0.803079	0.1071	0.1140	0.0103	0.000000	0.000000
2459499	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.055086	0.249298	-1.123886	0.169449	-0.471721	0.131327	-0.464143	-0.763379	0.1183	0.1351	0.0088	0.000000	0.000000
2459498	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.286570	-0.262440	-0.433492	0.041685	-0.306611	-0.020973	-0.877694	-0.200055	0.1336	0.1203	0.0150	0.000000	0.000000
2459497	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.175092	-0.035856	-0.020646	-0.057850	0.310681	-0.379132	-0.852718	-0.449462	0.1544	0.1390	0.0181	0.000000	0.000000
2459496	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.607660	-0.288252	-0.510225	0.214500	-0.433677	0.070479	-0.775076	-0.430238	0.9096	0.9190	0.3519	0.000000	0.000000
2459495	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.442272	-0.118670	-0.675696	0.085344	-0.515186	-0.101746	-0.787495	-0.210757	0.9051	0.9137	0.3903	0.000000	0.000000
2459494	digital_ok	0.00%	0.00%	0.00%	0.00%	94.74%	0.00%	-0.327147	0.086198	-1.029333	0.158740	-0.578446	-0.433831	-0.780267	-0.537901	0.8906	0.9016	0.4122	0.000000	0.000000
2459492	digital_ok	0.00%	0.00%	0.00%	0.00%	50.00%	0.00%	0.488601	-0.227574	0.353387	-0.040347	-0.104921	-1.002991	-0.486877	-0.738258	0.7536	0.8018	0.3289	0.443859	0.421944
2459491	digital_ok	0.00%	0.00%	0.00%	0.00%	50.00%	0.00%	-0.125829	-0.049327	0.606052	0.708306	0.186212	1.269567	-0.515433	-0.281092	0.7969	0.8190	0.2531	0.848418	0.767595
2459490	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	0.164105	-0.076469	0.476355	0.080141	-0.054712	-0.447383	-0.478670	-0.469873	0.7484	0.7993	0.3758	1.917499	1.733424
2459489	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	0.048952	0.086978	0.255795	0.349717	0.917715	-0.122820	-0.192491	-0.165829	0.7681	0.8080	0.3157	1.727402	1.706716
2459488	digital_ok	0.00%	0.00%	0.00%	0.00%	85.71%	0.00%	0.480102	-0.050631	0.058903	-0.038432	0.247748	0.016210	-0.456856	-0.638189	0.7689	0.8105	0.3537	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 185 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 185, Node 14:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 185: 2459595

Antenna 185: 2459594

Antenna 185: 2459593

Antenna 185: 2459592

Antenna 185: 2459591

Antenna 185: 2459590

Antenna 185: 2459589

Antenna 185: 2459588

Antenna 185: 2459587

Antenna 185: 2459586

Antenna 185: 2459585

Antenna 185: 2459584

Antenna 185: 2459583

Antenna 185: 2459582

Antenna 185: 2459581

Antenna 185: 2459580

Antenna 185: 2459579

Antenna 185: 2459578

Antenna 185: 2459577

Antenna 185: 2459576

Antenna 185: 2459575

Antenna 185: 2459574

Antenna 185: 2459573

Antenna 185: 2459572

Antenna 185: 2459571

Antenna 185: 2459570

Antenna 185: 2459569

Antenna 185: 2459566

Antenna 185: 2459565

Antenna 185: 2459564

Antenna 185: 2459563

Antenna 185: 2459562

Antenna 185: 2459561

Antenna 185: 2459560

Antenna 185: 2459559

Antenna 185: 2459558

Antenna 185: 2459556

Antenna 185: 2459552

Antenna 185: 2459551

Antenna 185: 2459549

Antenna 185: 2459542

Antenna 185: 2459541

Antenna 185: 2459540

Antenna 185: 2459536

Antenna 185: 2459535

Antenna 185: 2459534

Antenna 185: 2459533

Antenna 185: 2459532

Antenna 185: 2459530

Antenna 185: 2459527

Antenna 185: 2459524

Antenna 185: 2459523

Antenna 185: 2459522

Antenna 185: 2459513

Antenna 185: 2459508

Antenna 185: 2459506

Antenna 185: 2459505

Antenna 185: 2459503

Antenna 185: 2459501

Antenna 185: 2459500

Antenna 185: 2459499

Antenna 185: 2459498

Antenna 185: 2459497

Antenna 185: 2459496

Antenna 185: 2459495

Antenna 185: 2459494

Antenna 185: 2459492

Antenna 185: 2459491

Antenna 185: 2459490

Antenna 185: 2459489

Antenna 185: 2459488

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶